Modeling Fabric Movement for Future E-Textile Sensors.

Studies with e-textile sensors embedded in garments are typically performed on static and controlled phantom models that do not reflect the dynamic nature of wearables. Instead, our objective was to understand the noise e-textile sensors would experience during real-world scenarios. Three types of sleeves, made of loose, tight, and stretchy fabrics, were applied to a phantom arm, and the corresponding fabric movement was measured in three dimensions using physical markers and image-processing software. Our results showed that the stretchy fabrics allowed for the most consistent and predictable clothing-movement (average displacement of up to -2.3 ± 0.1 cm), followed by tight fabrics (up to -4.7 ± 0.2 cm), and loose fabrics (up to -3.6 ± 1.0 cm). In addition, the results demonstrated better performance of higher elasticity (average displacement of up to -2.3 ± 0.1 cm) over lower elasticity (average displacement of up to -3.8 ± 0.3 cm) stretchy fabrics. For a case study with an e-textile sensor that relies on wearable loops to monitor joint flexion, our modeling indicated errors as high as 65.7° for stretchy fabric with higher elasticity. The results from this study can (a) help quantify errors of e-textile sensors operating "in-the-wild," (b) inform decisions regarding the optimal type of clothing-material used, and (c) ultimately empower studies on noise calibration for diverse e-textile sensing applications.

Wrap-Around Wearable Coils for Seamless Monitoring of Joint Flexion.

OBJECTIVE: We introduce and validate a new class of wearable coils that seamlessly monitor joint flexion in the individual's natural environment while overcoming shortcomings in state-of-the-art. METHODS: Our approach relies on Faraday's law of induction and employs wrap-around transmit and receive coils that get angularly misaligned as the joint flexes. RESULTS: Simulation and in vitro measurement results for both copper and e-thread coils are in excellent agreement. As a proof-of-concept, a cylindrical arm model is considered and feasibility of monitoring the 0°-130° range of motion is confirmed. The operation frequency of 34 MHz is identified as optimal, bringing forward reduced power requirements, enhanced angular resolution, and extreme robustness to tissue dielectric property variations. Performance benchmarking versus state-of-the-art inertial measurement units shows equivalent or superior performance, particularly for flexion angles greater than 20°. Design guidelines and safety considerations are also explored. CONCLUSION: Contrary to "gold-standard" camera-based motion capture, the reported approach is not restricted to contrived environments. Concurrently, it does not suffer from integration drift (unlike inertial measurement units), it does not require line-of-sight (unlike time-of-flight sensors), and it does not restrict natural joint movement (unlike bending sensors). SIGNIFICANCE: The reported approach is envisioned to be seamlessly integrated into garments and, eventually, redefine the way joint flexion is monitored at present. This promises unprecedented opportunities for rehabilitation, sports, gestural interaction, and more.